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Spatial and temporal assessment of responder exposure to snag hazards in post-fire environments

Dunn, Christopher J., O'Connor, Christopher D., Reilly, Matthew J., Calkin, Dave E., Thompson, Matthew P.·2019·Forest Ecology and Management
DOI 10.1016/j.foreco.2019.03.035
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Abstract

Researchers and managers increasingly recognize enterprise risk management as critical to addressing contemporary fire management challenges. Quantitative wildfire risk assessments contribute by parsing and mapping potentially contradictory positive and negative fire effects. However, these assessments disregard risks to fire responders because they only address social and ecological resources and assets. In this study, we begin to overcome this deficiency by using a novel modeling approach that integrates remote sensing, field inventories, imputation-based vegetation modeling, and empirical models to quantify post-fire snag hazard in space and time. Snag hazard increased significantly immediately post-fire, with severe or extreme hazard conditions accounting for 47%, 83%, and 91% of areas burned at low, moderate and high-severity fire, respectively. Patch-size of severe or extreme hazard positively correlated with fire size, exceeding >20,000 ha (60% of our largest fire) 10-years post-fire when reburn becomes more likely. After 10 years, snag hazard declined rapidly as snags fell or fragmented, but severe or extreme hazard persisted for 20, 30 and 35 years in portions of the low, moderate and high-severity fire areas. Because forests are denser and wildfires burn with greater severity than historically, these hazardous conditions may represent novel management challenges where risk of injury or death to responders outweighs the benefits of directly engaging the fire. Mapping…

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Research works printed but not linked: 51

  1. Abatzoglou, 2016, Impact of anthropogenic climate change on wildfire across western US forests, Proc. Natl. Acad. Sci., 113, 11770, 10.1073/pnas.1607171113 · DOI · Paper page
  2. Agee, 2005, Basic principles of forest fuel reduction treatments, For. Ecol. Manage., 211, 83, 10.1016/j.foreco.2005.01.034 · DOI · Paper page
  3. Bates, 2015, Fitting linear mixed-effects models using lme4, J. Stat. Softw., 67, 1, 10.18637/jss.v067.i01 · DOI · Paper page
  4. Bull, E.L., Parks, C.G., Torgersen, T.R., 1997. Trees and Logs Important to Wildlife in the Interior Columbia River Basin. USDA Forest Service General Technical Report PNW-GTR-391. Pacific Northwest Research Station, Portland, OR. · DOI
  5. Butler, 2014, Wildland firefighter safety zones: a review of past science and summary of future needs, Int. J. Wildland Fire, 23, 295, 10.1071/WF13021 · DOI
  6. Canton-Thompson, 2008, External human factors in incident management team decision making and their effect on large fire suppression expenditures, J. Forest., 106, 416, 10.1093/jof/106.8.416 · DOI · Paper page
  7. Charnley, 2017, Diversity in forest management to reduce wildfire losses: implications for resilience, Ecol. Soc., 22, 22, 10.5751/ES-08753-220122 · DOI
  8. Collins, 2009, Interactions among wildland fires in a long-established sierra nevada natural fire area, Ecosystems, 12, 114, 10.1007/s10021-008-9211-7 · DOI
  9. Dunn, 2012, Temporal dynamics and decay of coarse wood in early seral habitats of dry-mixed conbifer forests in Oregon’s Eastern Cascades, For. Ecol. Manage., 276, 71, 10.1016/j.foreco.2012.03.013 · DOI
  10. Dunn, 2015, Modeling the direct effects of salvage logging on longterm temporal fuel dynamics in dry-mixed conifer forests, For. Ecol. Manage., 341, 93, 10.1016/j.foreco.2015.01.002 · DOI
  11. Dunn, 2016, Tree mortality and structural change following mixed-severity fire in Pseudotsuga forests of Oregon’s western Cascades, USA, For. Ecol. Manage., 341, 93, 10.1016/j.foreco.2015.01.002 · DOI
  12. Dunn, 2017, Towards enhanced risk management: planning, decision making and monitoring of US wildfire response, Int. J. Wildland Fire, 26, 551, 10.1071/WF17089 · DOI
  13. Dunn, 2017, A framework for developing safe and effective large-fire response in a new fire management paradigm, For. Ecol. Manage., 404, 184, 10.1016/j.foreco.2017.08.039 · DOI
  14. Franklin, 1987, Tree death as an ecological process, Bioscience, 37, 550, 10.2307/1310665 · DOI
  15. Grayson, 2019, Persistence of fire-killed conifer snags in California, USA, Fire Ecol., 15, 10.1186/s42408-018-0007-7 · DOI
  16. Haas, 2013, A national approach for integrating wildfire simulation modeling into Wildland Urban Interface risk assessments within the United States, Landscape Urban Plann., 119, 44, 10.1016/j.landurbplan.2013.06.011 · DOI
  17. Harmon, 1986, Ecology of coarse woody debris in temperate ecosystems, Adv. Ecol. Res., 15, 133, 10.1016/S0065-2504(08)60121-X · DOI
  18. Johnston, 2018, Restoring historical forest conditions in a diverse inland Pacific Northwest landscape, Ecosphere, 9, 10.1002/ecs2.2400 · DOI
  19. Johnston, 2017, Forest succession along a productivity gradient following fire exclusion, For. Ecol. Manage., 392, 45, 10.1016/j.foreco.2017.02.050 · DOI
  20. Kennedy, 2010, Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. Landtrer – temporal segmentation algorithms, Remote Sens. Environ., 114, 2897, 10.1016/j.rse.2010.07.008 · DOI
  21. Larson, 2013, Latent resilience in ponderosa pine forest: effects of resumed frequent fire, Ecol. Appl., 23, 1243, 10.1890/13-0066.1 · DOI
  22. Max, T.A., Schreuder, H.T., Hazard, J.W., Oswald, D.D., Teply, J., Alegria, J. 1996. The Pacific Northwest Region vegetation and inventory monitoring system. Res. Pap. PNW-RP-493. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, p. 22. · DOI
  23. McDowell, 2015, Multi-scale predictions of massive conifer mortality due to chronic temperature rise, Nat. Clim. Change, 6, 295, 10.1038/nclimate2873 · DOI
  24. Meddens, 2012, Spatiotemporal patterns of observed bark beetle-caused tree mortality in British Columbia and the western United States, Ecol. Appl., 22, 1876, 10.1890/11-1785.1 · DOI
  25. Merschel, 2014, Mixed-conifer forests of centeral Oregon: effects of logging and fire exclusion vary with environment, Ecol. Appl., 24, 1670, 10.1890/13-1585.1 · DOI
  26. Miller, 2007, Quantifying burn severity in a heterogeneous landscape with a relative version of the delta normalized burn ratio (dNBR), Remote Sens. Environ., 109, 66, 10.1016/j.rse.2006.12.006 · DOI
  27. Naficy, 2010, Interactive effects of historical logging and fire exclusion on ponderosa pine forest structure in the northern Rockies, Ecol. Appl., 20, 1851, 10.1890/09-0217.1 · DOI
  28. North, 2015, Constraints on mechanized treatment significantly limit mechanical fuels reduction extent in the sierra nevada, J. Forest., 113, 40, 10.5849/jof.14-058 · DOI
  29. O’Connor, 2017, An empirical machine learning method for predicting potential fire control locations for pre-fire planning and operational fire management, Int. J. Wildland Fire, 26, 587, 10.1071/WF16135 · DOI · Paper page
  30. O’Connor, 2016, Getting ahead of the wildfire problem: quantifying and mapping management challenges and opportunities, Goesciences, 6, 1
  31. Ohmann, 2002, Predictive mapping of forest composition and structure with direct gradient analysis and nearest-neighbor imputation in coastal Oregon, U.S.A, Can. J. For. Res., 32, 725, 10.1139/x02-011 · DOI
  32. Ohmann, 2012, Mapping change of older forest with nearest-neighbor imputation and Landsat timeseries, For. Ecol. Manage., 272, 13, 10.1016/j.foreco.2011.09.021 · DOI
  33. Page, 2013, Wildfire’s resistance to control in mountain pine beetle-attacked lodgepole pine forests, Forestry Chronicle, 89, 783, 10.5558/tfc2013-141 · DOI · Paper page
  34. Parks, 2016, Wildland fire limits subsequent fire occurrence, Int. J. Wildland Fire, 25, 182, 10.1071/WF15107 · DOI
  35. Parks, 2014, Previous fires moderate burn severity of subsequent wildland fires in two large western US wilderness areas, Ecosystems, 17, 29, 10.1007/s10021-013-9704-x · DOI
  36. Reilly, M.J., Spies, T.A. 2015. Regional Variation in Forest Structure and Development in Oregon, Washington, and Inland Northern California, USA. Ecosphere 6:art192. · DOI
  37. Reilly, 2017, Contemporary patterns of fire extent and severity in forests of the Pacific Northwest, USA (1985–2010), Ecosphere, 8, 10.1002/ecs2.1695 · DOI
  38. Reilly, 2018, Cumulative effects of wildfires on forest dynamics in the eastern Cascade Mountains, USA, Ecol. Appl., 28, 291, 10.1002/eap.1644 · DOI
  39. Riley, 2016, Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots, Ecosphere, 7, 10.1002/ecs2.1472 · DOI
  40. Rodriguez y Silva, 2014, A methodology for determing operational priorities for prevention and suppression of wildland fires, Int. J. Wildland Fire, 23, 544, 10.1071/WF13063 · DOI
  41. Stephens, 2014, Temperate and boreal forest mega-fires: characteristics and challenges, Front. Ecol. Environ., 12, 115, 10.1890/120332 · DOI
  42. Stevens, 2017, Changing spatial patterns of stand-replacing fire in California conifer forests, For. Ecol. Manage., 406, 29, 10.1016/j.foreco.2017.08.051 · DOI · Paper page
  43. Stevens-Rumann, 2018, Evidence for declining forest resilience to wildfires under climate change, Ecol. Lett., 21, 243, 10.1111/ele.12889 · DOI · Paper page
  44. Swanson, 2010, The forgotten stage of forest succession: early-successional ecosystems on forest sites, Front. Ecol. Evniron., 9, 1
  45. Ter Braak, 1986, Canonical correspondence analysis: a new eigenvector technique for multivarite direct gradient analysis, Ecology, 67, 1167, 10.2307/1938672 · DOI
  46. Thompson, 2011, Uncertainty and risk in wildand fire managemetn: a review. 2011, J. Environ. Manage., 92, 1895, 10.1016/j.jenvman.2011.03.015 · DOI · Paper page
  47. Thompson, 2015, Wildfires: Systemic changes required, Science, 350, 920, 10.1126/science.350.6263.920-b · DOI
  48. Thompson, 2016, Quantifying the influence of previously burned areas on suppression effectiveness and avoided exposure: a case study of the Las Conchas Fire, Int. J. Wildland Fire, 25, 167, 10.1071/WF14216 · DOI
  49. Thompson, 2018, Rethinking the wildland fire management system, J. Forest., 116, 382, 10.1093/jofore/fvy020 · DOI
  50. Tinker, 2000, Coarse woody debris following fire and logging in Wyoming lodgepole pine forests, Ecosystems, 3, 472, 10.1007/s100210000041 · DOI
  51. Zald, 2018, Sever fire weather and intensive forest management increase fire severity in a multi-ownership landscape, Ecol. Appl., 28, 1068, 10.1002/eap.1710 · DOI

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Metadata

Authors
Dunn, C. J., O'Connor, C. D., Reilly, M. J., Calkin, D. E., & Thompson, M. P.
Venue
Forest Ecology and Management
Publisher
Elsevier BV
Published
2019-06
Volume
441
Pages
202-214
ISSN
0378-1127
DOI
10.1016/j.foreco.2019.03.035
Cited by
48
References
5
Language
en
Licence
Funders
Research Joint Venture (No. 15-JV-11221636-059)

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